chickadee » nanograd » make-dense-layer

Creates a fully connected layer. Weights start as uniform random values scaled by sqrt(2 / input-size); biases start at zero.

input-size

number of input features

output-size

number of output features

activation

activation object (default identity)

use-bias

whether to include a bias term (default #t)

dtype

'f32 or 'f64 (default 'f32)

name

layer name

Input shapes:

• 1-D: (input_size) -> output: (output_size)
• 2-D: (batch_size, input_size) -> output: (batch_size, output_size)

For 2-D inputs, the layer uses one BLAS GEMM for the whole batch.

(define layer (make-dense-layer 784 128
                                activation: (make-relu)
                                name: "Hidden1"))

; Single input
(define x (make-tensor32 (make-f32vector 784) '(784)))
(define output (forward layer x))  ; Shape: (128)

; Batch input
(define batch-x (make-tensor32 (make-f32vector (* 32 784)) '(32 784)))
(define batch-output (forward layer batch-x))  ; Shape: (32, 128)